FREE TRIAL

Correlating Photogrammetry and MWD: Toward Predictive Rock Mass Characterization

In mining, every decision rests on the quality of insight into the rock mass. The more data engineers can extract — about its structures, discontinuities, and concealed weaknesses — the safer the operation, the more stable the excavation, and the more cost-effective the project.

Yet, capturing the full story of the rock mass has long been elusive: traditional methods offer partial truths, surface-based imaging stops at the façade, and drilling alone cannot tell the whole tale.

Today, that limitation is dissolving. By correlating 3GSM’s ShapeMetriX photogrammetry with measurement-while-drilling (MWD) data, engineers can now access a more complete picture of rock mass conditions, bringing unprecedented clarity and confidence to design and operational decisions.

The Challenge of Characterization

Traditional mapping methods — such as manual scanlines, window surveys, and compass measurements — remain among the most trusted and widely used approaches for structural mapping. Alongside them, contact-free techniques like photogrammetry have revolutionized the field, offering a highly reliable way to capture the geometry of the exposed rock face in remarkable detail. MWD data, by contrast, records the internal responses of rock to penetration along every borehole. Yet until now, these two perspectives have often remained disconnected. A study published in Engineering Geology (Manzoor et al., 2020) brought a new perspective by correlating ShapeMetriX’s structural mapping with MWD data recorded at LKAB’s Leveäniemi mine in Sweden.

The Study at Leveäniemi Mine 

At LKAB’s Leveäniemi iron ore mine in northern Sweden, researchers set out to unify the surface and the subsurface. ShapeMetriX generated high-resolution 3D models from stereoscopic images of nine bench faces, each carefully scaled and georeferenced. Using the Analyst module, the models were examined to characterize structural features — dip, dip direction, trace length, exposed surface area, and discontinuity spacing. This structural dataset was extracted along scanlines drawn directly at borehole locations, enabling a precise alignment between photogrammetric observations and the corresponding MWD records. 

Figure 1. Leveäniemi open pit mine with marked walls used for this study 

Simultaneously, MWD data was collected from 473 boreholes, capturing key drilling parameters: penetration rate, rotation pressure, feed pressure, and percussive pressure. After removing noise from collaring, rod changes, and faulty readings, the team found that penetration rate and rotation pressure reliably reflected changes in the rock mass – while feed and percussive pressures mainly tracked equipment behavior. 

Figure 2. 3D model of a bench face with joints, exposed surfaces and scanlines (white dotted lines) marked on the surface

But data alone does not reveal truth; it must be interwoven. The real breakthrough of the study came in linking ShapeMetriX’s surface models with the subsurface story captured in MWD records.
 

Linking Structural Data with MWD Results 

Where photogrammetry maps the anatomy of the rock mass, MWD captures its internal response. ShapeMetriX enabled rigorous identification of surface structures, while the MWD logs revealed variations in resistance every 5 centimeters along each borehole. 

To bridge these two worlds, researchers aligned ShapeMetriX scanlines with borehole coordinates, matching intersections in the 3D models to depths in the MWD logs.  This careful correlation transformed the analysis from a simple comparison of datasets into a true dialogue between structure and response. 

The insights were revelatory. 

  • Fractures and joints showed as modest, localized increases in penetration rate and rotation pressure at the exact depths identified in ShapeMetriX – rising from averages near 0.85 m/min to about 2 m/min for penetration, and from roughly 60.8 bar to 70 bar in rotation pressure. Subtle though they appear, these spikes mark the difference between intact rock and discontinuities within the rock mass. 
Figure 3. Rise in penetration rate (PR) and rotation pressure (PR) at fracture/joint location
  • Cavities and infilled voids produced broader fluctuations across multiple parameters. Here, MWD data was “noisy,” revealing zones with loose or removable material, essentially confirming what ShapeMetriX had mapped – these were not fractures but cavities or wedges with loose or removable material.
Figure 4. MWD data from two different holes showing fluctuations in all the drilling parameters
  • Closely spaced bedding planes and foliations, in contrast, altered the baseline. Rather than abrupt spikes, they raised mean penetration rates (in one case to ~0.95 m/min) and shifted drilling resistance gradually across intervals. The structural fabric mapped in ShapeMetriX mirrored these subdued but systematic changes, revealing zones of weakened rock. 
Figure 5. MWD data plot of a borehole and rock face image for poor rock conditions

This correlation between the mapped and the measured data does more than validate ShapeMetriX and MWD independently. It demonstrates a convergence: rock mass structures are no longer isolated observations or abstract datasets but integrated indicators, each reinforcing the other. The ability to see a joint and simultaneously know its effect on drilling resistance shifts geotechnical understanding from descriptive to predictive. 

The study also underscored contrasts between wall conditions. In the pre-split wall, with minimal blast-induced fractures and visible half-casts, correlations were strong and localized to major joints or cavities. In the poor-quality wall, with closely spaced structures, MWD traces showed both abrupt variations and systematic baseline shifts. 

Figure 6. Variations in penetration rate (PR) and rotation pressure (RP) along with corresponding structures

Together, these results highlight how combining ShapeMetriX and MWD not only diagnoses existing structures but prescribes how design decisions such as charging, blasting, and wall stability, can be adapted to local conditions.

Implications for Mining Practice 

Armed with these insights, mine planners gain the ability to: 

  • Tailor blast designs by modulating explosive charges to match localized rock conditions. 
  • Optimize fragmentation for smoother downstream handling. 
  • Stabilize walls by anticipating discontinuities before they manifest as hazards. 
  • Refine geological models by integrating both surface and subsurface truths into a unified framework.
     

Conclusion 

What was once divided (the mapped and the measured) now reads as a single narrative. By coupling ShapeMetriX’s precision with the depth-wise sensitivity of MWD data, mines gain predictive mastery of rock mass behavior. The study also points forward: MWD systems must continue to improve in quality and consistency, but the trajectory is clear. With ShapeMetriX, mines move from description to anticipation, from uncertainty to mastery. This evolution does not just define better geotechnics; it defines the future of mining, and it is a future 3GSM is engineering.